#!/usr/bin/python3
# coding=utf-8

# Copyright (c) 2025 Huawei Technologies Co., Ltd.
# This file is a part of the CANN Open Software.
# Licensed under CANN Open Software License Agreement Version 1.0 (the "License").
# Please refer to the License for details. You may not use this file except in compliance with the License.
# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
# INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
# See LICENSE in the root of the software repository for the full text of the License.
# ======================================================================================================================

import os

import numpy as np


def gen_golden_data(work_path, params=None):
    input_path = os.path.join(work_path, "input")
    if not os.path.exists(input_path):
        os.makedirs(input_path)
    output_path = os.path.join(work_path, "output")
    if not os.path.exists(output_path):
        os.makedirs(output_path)

    if params:
        m, n, k, is_bias = params.m, params.n, params.k, params.isBias
    else:
        m, n, k, is_bias = 7680, 480, 320, True

    a1_gm = np.random.uniform(-10, 10, [m, k]).reshape([m, k]).astype(np.float16)
    b1_gm = np.random.uniform(-10, 10, [k, n]).reshape([k, n]).astype(np.float16)
    a2_gm = np.random.uniform(-10, 10, [m, k]).reshape([m, k]).astype(np.float16)
    b2_gm = np.random.uniform(-10, 10, [k, n]).reshape([k, n]).astype(np.float16)
    bias_gm = np.random.uniform(-10, 10, [n]).reshape([n]).astype(np.float32)

    if is_bias:
        golden_1 = np.matmul(a1_gm.astype(np.float32), b1_gm.astype(np.float32), dtype=np.float32) + bias_gm
        golden_2 = np.matmul(a2_gm.astype(np.float32), b2_gm.astype(np.float32), dtype=np.float32) + bias_gm
    else:
        golden_1 = np.matmul(a1_gm.astype(np.float32), b1_gm.astype(np.float32), dtype=np.float32)
        golden_2 = np.matmul(a2_gm.astype(np.float32), b2_gm.astype(np.float32), dtype=np.float32)

    a1_gm.tofile(os.path.join(input_path, "a1_gm.bin"))
    b1_gm.tofile(os.path.join(input_path, "b1_gm.bin"))
    a2_gm.tofile(os.path.join(input_path, "a2_gm.bin"))
    b2_gm.tofile(os.path.join(input_path, "b2_gm.bin"))
    bias_gm.tofile(os.path.join(input_path, "bias_gm.bin"))
    golden_1.tofile(os.path.join(output_path, "golden_1.bin"))
    golden_2.tofile(os.path.join(output_path, "golden_2.bin"))


if __name__ == "__main__":
    gen_golden_data(os.getcwd())
